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Higher-order correlations reveal complex memory in temporal hypergraphs
Title / Series / Name
Publication Volume
Publication Issue
Pages
Editors
Keywords
General Chemistry
General Biochemistry,Genetics and Molecular Biology
General Physics and Astronomy
General Biochemistry,Genetics and Molecular Biology
General Physics and Astronomy
URI
https://hdl.handle.net/20.500.14018/26676
Abstract
Many real-world complex systems are characterized by interactions in groups that change in time. Current temporal network approaches, however, are unable to describe group dynamics, as they are based on pairwise interactions only. Here, we use time-varying hypergraphs to describe such systems, and we introduce a framework based on higher-order correlations to characterize their temporal organization. The analysis of human interaction data reveals the existence of coherent and interdependent mesoscopic structures, thus capturing aggregation, fragmentation and nucleation processes in social systems. We introduce a model of temporal hypergraphs with non-Markovian group interactions, which reveals complex memory as a fundamental mechanism underlying the emerging pattern in the data.
Topic
Publisher
Place of Publication
Type
Journal article
Date
2024-06-04
Language
ISBN
Identifiers
10.1038/s41467-024-48578-6